Technical hiring at software companies proceeds through three levels of filters:
1. Sourcing (recruiters find candidates for technical people to interview)
2. Screening (generally one or two phone interviews, leading to the term “phone screen”)
3. Onsite (several interviews in person)
There are some exceptions to this rule — campus hiring often skips the second, and if you have senior executives who like to meddle, they can constitute a fourth filter — but practically speaking what matters to the prospective employee is whether recruiters can find you and whether technical people approve of your interview performance.
There is a large male/female gap in computer professions. The links from my previous post show something interesting:
|Computer and mathematical occupations||26.1|
|Software developers, applications and systems software||19.7|
|Network and computer systems administrators|| 17.3|
I picked those job titles as they correspond best to Google’s technical jobs.
We see at Google’s Diversity site that only 17% of those positions are filled by women. Explaining the gender gap on factors external to women themselves (i.e., bias) is likely a sack of crap. Are we really to believe that Google is more biased than the average
(Do you know how many top executives I personally have seen toe the SJW line on racism/sexism/homophobia?
All of them.)
Back to math. To explain the gender gap as caused by unconscious bias, we must explain how our three levels of filters can eliminate 75% or more of the qualified females.
I have never seen any diversity advocate propose even approximate numbers for this supposed phenomenon. Are the recruiters not finding women? That’s hard to believe, given that recruiters are employed on the basis of their ability to find even semi-plausible candidates. Also recruiters don’t impress me as the most reactionary bunch. They happily imbibe the social justice theory du jour. Many companies already have teams of recruiters whose role is to source women and minorities.
Are we really to believe that an organization which is officially committed to gender and race equity, with some of its efforts restricted only to recruiting women and minorities, somehow does a worse job of finding such candidates than if they just selected resumes at random?
Does the filtering happen during the technical interview process? I can think of 3 objections:
1. Interviewers themselves would notice. “It’s strange that although my coworkers are mostly male, I interview a lot of women” said no one ever.
2. Female engineers would have a very high unemployment rate. Again, people would notice. You’d also think somebody would try to take advantage of this vast pool of untapped talent.
3. If there were systematic reasons why ostensibly objective technical interviews were in fact skewed against women (and minorities), someone would have developed training specifically to address that case, rather than non-specific bullshit that accomplishes nothing other than to assuage liberal guilt. Think about it: “unconscious bias” is an admission that there is no such thing as “actionable and identifiable bias.”
Before we leave the arena of numbers, please note that Google — which uses the term Social Justice non-ironically (“Join fellow Googlers for social justice-inspired volunteer projects near you on Martin Luther King Day!”) — has a technical workforce that is 1% black. The black percentages for the BLS categories I listed above are 4 to 8%.
Would the Unconscious Biasers like to state, with a straight face, that Google is 4 to 8 times more prejudiced than the industry at large?
Enough numbers. Let’s talk about prejudice!
Here are the specimens that I am supposedly privileging, in my quest to prevent women from being hired:
– The Indian with terrible BO, a ridiculous mustache, and a belief that his matriculation from IIT makes him superior to plebian humans.
– The Chinaman who can barely speak English, will never be able to write colloquially even if he lives here a decade, and is so soft and ovine as to instill in you a secret sympathy for Genghis Khan.
– The skinny twerp who watches too much anime. (That is to say, any anime.)
Everyone in America has been socialized, for decades, to believe in female equality and opportunity. Blaming “bias” for the technological gender gap is equivalent to a Soviet agronomy minister blaming “wreckers” for the 12th consecutive bad harvest.